# GPT-5.5 vs MiMo-V2.6-Pro

> GPT-5.5 is the stronger model overall, scoring 63.4 to 46.7 on the Noometry Index. MiMo-V2.6-Pro costs 21× less per token, which makes it the better buy when GPT-5.5's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/gpt-5-5-vs-mimo-v2-6-pro
- Last updated: 2026-10-10
- Shared benchmarks: 14

## Summary

- They share 14 benchmarks with published results for both. GPT-5.5 scores higher in 7 categories and MiMo-V2.6-Pro in 2 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in math, where GPT-5.5 leads 81.5 to 37.9.
- MiMo-V2.6-Pro is cheaper at $0.43 / $0.87 per million input/output tokens, against $5 / $30 for GPT-5.5.
- GPT-5.5 accepts more context: 1.05M tokens versus 1.05M.
- MiMo-V2.6-Pro has downloadable open weights; the other is API-only.

## Snapshot

| | GPT-5.5 | MiMo-V2.6-Pro |
|---|---|---|
| Provider | OpenAI | Xiaomi |
| Noometry Index | 63.4 | 46.7 |
| Rank | 8 | 55 |
| Context | 1.05M | 1.05M |
| Input $/M | $5 | $0.43 |
| Output $/M | $30 | $0.87 |
| Weights | Proprietary | Open |

## Coding

- GPT-5.5: 58.3 (#13)
- MiMo-V2.6-Pro: 53.2 (#27)

| Benchmark | GPT-5.5 | MiMo-V2.6-Pro |
|---|---|---|
| LMArena WebDev | 1512 | 1618 |
| LMArena Coding | 1494 | 1538 |
| SWE-bench Verified | 80.6% | — |
| DeepSWE | 67% | — |
| FrontierCode | 43% | — |
| SciCode | 56.1% | — |
| GSO | 40.2% | — |
| WeirdML | 84.9% | — |
| MirrorCode | 10% | — |
| ALE-Bench | 1,943 | — |

## Agentic & Tool Use

- GPT-5.5: 50.7 (#6)
- MiMo-V2.6-Pro: —

| Benchmark | GPT-5.5 | MiMo-V2.6-Pro |
|---|---|---|
| Terminal-Bench | 84.7% | — |
| APEX-Agents | 55.1% | — |
| OSWorld 2.0 | 13% | — |
| Remote Labor Index | 6.3% | — |
| τ²-bench Banking | 44.6% | — |
| DeepResearch Bench | 54% | — |
| PostTrainBench | 27.2% | — |
| ExploitBench | 47.4% | — |
| GBAEval | 53.2% | — |
| GDP.pdf | 26% | — |
| LMArena Search | 1242 | — |
| Vending-Bench 2 | 7,524 | — |

## Reasoning

- GPT-5.5: 72.7 (#8)
- MiMo-V2.6-Pro: 30.4 (#76)

| Benchmark | GPT-5.5 | MiMo-V2.6-Pro |
|---|---|---|
| LMArena Hard Prompts | 1489 | 1511 |
| ARC-AGI-2 | 85% | — |
| SimpleBench | 69% | — |
| Kagi LLM Benchmark | 88.8% | — |
| NYT Connections (extended) | 96.2% | — |
| ARC-AGI-1 | 95% | — |
| CritPt | 27.1% | — |
| Chess Puzzles | 54% | — |
| EBR-Bench | 34.3% | — |
| Mystery Game Puzzles | 56% | — |
| DTBench | 96% | — |
| LMCA | 54.3% | — |
| Surface Evolver Bench | 88.1% | — |
| Bench to the Future 3 | 0.14 | — |
| Epoch Capabilities Index | 159.25 | — |
| ForecastBench | 60.6 | — |

## Math

- GPT-5.5: 81.5 (#9)
- MiMo-V2.6-Pro: 37.9 (#91)

| Benchmark | GPT-5.5 | MiMo-V2.6-Pro |
|---|---|---|
| LMArena Math | 1486 | 1497 |
| FrontierMath (Tiers 1-3) | 85.3% | — |
| FrontierMath Tier 4 | 72.5% | — |
| MathArena Final-Answer Competitions | 94.3% | — |
| OTIS Mock AIME 2024-2025 | 100% | — |
| ProofBench | 50% | — |
| FrontierMath (Feb 2025 set) | 51.7% | — |
| FrontierMath Erdős | 0% | — |
| FrontierMath Tier 4 (v1) | 35.4% | — |

## Knowledge

- GPT-5.5: 64.4 (#14)
- MiMo-V2.6-Pro: 43.0 (#85)

| Benchmark | GPT-5.5 | MiMo-V2.6-Pro |
|---|---|---|
| LMArena Expert | 1508 | 1548 |
| GPQA Diamond | 94% | — |
| SimpleQA Verified | 63% | — |
| Vectara Hallucination Rate | 9.3% | — |

## Multimodal

- GPT-5.5: 47.1 (#11)
- MiMo-V2.6-Pro: 40.2 (#40)

| Benchmark | GPT-5.5 | MiMo-V2.6-Pro |
|---|---|---|
| LMArena Vision | 1297 | 1265 |
| Blueprint-Bench 2 | 36.2% | — |
| Furniture Assembly | 44.2% | — |
| LMArena Document | 1486 | — |

## Multilingual

- GPT-5.5: 56.5 (#19)
- MiMo-V2.6-Pro: 57.0 (#15)

| Benchmark | GPT-5.5 | MiMo-V2.6-Pro |
|---|---|---|
| LMArena Non-English | 1467 | 1474 |
| LMArena Chinese | 1535 | 1532 |
| LMArena Russian | 1473 | 1481 |
| LMArena French | 1486 | — |
| LMArena German | 1478 | — |
| LMArena Japanese | 1498 | — |
| LMArena Korean | 1461 | — |
| LMArena Spanish | 1469 | — |

## Instruction Following

- GPT-5.5: 77.7 (#18)
- MiMo-V2.6-Pro: 78.2 (#10)

| Benchmark | GPT-5.5 | MiMo-V2.6-Pro |
|---|---|---|
| LMArena Instruction Following | 1479 | 1490 |

## Long Context

- GPT-5.5: 48.3 (#12)
- MiMo-V2.6-Pro: 46.0 (#26)

| Benchmark | GPT-5.5 | MiMo-V2.6-Pro |
|---|---|---|
| LMArena Longer Query | 1484 | 1500 |
| CL-bench Life | 22.2% | — |

## Writing & Preference

- GPT-5.5: 72.8 (#13)
- MiMo-V2.6-Pro: 66.9 (#32)

| Benchmark | GPT-5.5 | MiMo-V2.6-Pro |
|---|---|---|
| LMArena Text | 1471 | 1491 |
| LMArena Creative Writing | 1455 | 1465 |
| LMArena Multi-Turn | 1477 | 1463 |
| EQ-Bench Creative Writing | 1844 | — |
| EQ-Bench 4 | 1315 | — |

## FAQ

### Is GPT-5.5 better than MiMo-V2.6-Pro?

GPT-5.5 is the stronger model overall, scoring 63.4 to 46.7 on the Noometry Index. MiMo-V2.6-Pro costs 21× less per token, which makes it the better buy when GPT-5.5's lead doesn't matter for your workload.

### Which is cheaper, GPT-5.5 or MiMo-V2.6-Pro?

MiMo-V2.6-Pro is cheaper. It lists at $0.43 per million input tokens and $0.87 per million output tokens; GPT-5.5 lists at $5 and $30.

### Is GPT-5.5 or MiMo-V2.6-Pro better for coding?

GPT-5.5 scores higher on coding benchmarks: 58.3 versus 53.2 in the Noometry coding category.

### Which has the bigger context window?

GPT-5.5 does, with 1.05M tokens against 1.05M.

### How many benchmarks do GPT-5.5 and MiMo-V2.6-Pro share?

14 benchmarks have published results for both models. GPT-5.5 has 71 scored results on Noometry and MiMo-V2.6-Pro has 14.